1. Field
The present invention relates to processing impulses using time domain representations, and, more particularly, to systems and methods of processing acoustic impulses such as bullet pulses and/or muzzle pulses in association with time domain representations.
2. Description of Related Information
Impulse processing, such as that associated with acoustic gunshot location systems, typically detects the impulsive sounds generated by the passing of a supersonic projectile and/or those sounds generated by the muzzle blast of the gun. The relative times of arrival of these pulses are used to compute the location a variety of algorithms well-known to those skilled in the art. If the microphone position and arrival time of each pulse are accurately measured on several sensors and the correct set of pulses is picked for location, highly accurate location results can be obtained. However if incorrect pulses are selected and passed to the location algorithms (for example, trying to locating on three direct pulse and one echo pulse, or four pulses from the first shot in a three-shot incident and one pulse from the second shot), wildly inaccurate results are often obtained. Thus it is of vital importance to associate each pulse with a specific shot and use only the pulses generated by a specific shot in the process of locating where that shot was fired.
A particularly challenging case is that where multiple rounds are fired from a supersonic assault rifle, such as an AK-47 or M-16. These firearms are capable of firing a great number of high-velocity rounds each second. Because the bullets significantly exceed the speed of sound, they generate a supersonic shock wave as they travel, with the result that a sensor placed near the path of the projectile will pick up at least two pulses (i.e., one bullet pulse, followed later by a slower “sonic” muzzle pulse) for each shot fired.
While the muzzle pulse travels at a constant velocity (the speed of sound) from the shooter to the sensor, the bullet pulse follows a time-minimizing path that depends on the velocity of the projectile and the aim angle of the shooter with respect to the sensor. The time spacing between bullet and muzzle pulses can vary between 0 (when the shooter is firing perpendicular to the sensor) and the shooter-sensor spacing divided by the difference between the projectile velocity and the speed of sound (when the shooter is firing directly at the sensor.) Since the aim angle is different for each sensor in the array, the bullet-muzzle pulse spacing also differs on each sensor.
Selection of the correct pulse may be further complicated by the presence of spurious pulses from reverberation and echoes that are frequently found following both bullet and muzzle pulses. Finally, the direct path bullet or muzzle pulse may be absent from the acoustic signal entirely. For these reasons, inter alia, features and functionality consistent with determining the time offsets of each channel and thus determining which pulse are associated with each shot are significantly innovative in systems and methods that seek to accurately locate acoustic gunshots.
While there is no constant spacing between bullet and muzzle pulses from a given shot, the spacing between muzzle pulses is invariant when shooter and sensor are stationary. Further, the time difference on each channel is the same as the time difference between trigger pulls. (The spacing is slightly increased or decreased when shooter or sensor are in relative motion.) Similarly, the spacing between bullet pulses is invariant when shooter and sensor are stationary and the aim point of the shooter is fixed.
Even with automatic weapons, there are usually slight differences in the time between each shot. This is caused by the variable timing of the trigger pulls by the shooter or, in fully automatic mode, by self-heating and reduction in cleanliness of the weapon. The spacing between shots thus forms a fingerprint that can be used to align time domain signatures from different sensors when two or more shots are fired.
A standard technique for aligning two time-domain signals is to take their cross-correlation. The position for which the cross-correlation is maximized is the point of maximum similarity between the two signals. This is an effective technique when the microphones are close together (e.g., less than 10 ft) because the audio signals heard by the microphones are fairly similar. As such, this technique is frequently used to determine the relative times of arrival, and thus the azimuth of arrival, from sensors comprised of arrays of microphones.
Direct cross-correlation of the audio signals has many drawbacks and disadvantages, however, when the microphones are far apart as is the case in many practical gunshot location systems. These disadvantages may include, for example:                1. The time-domain signals from distributed sensors must be delivered to a common computational platform for cross-correlation. Because of the size of the audio signals, this is expensive in terms of communication bandwidth.        2. Signals from the same weapon discharge may sound very different on different sensors. For example, one sensor might detect a gunshot through the a copse of trees while another gets a direct signal across a field. Such disparate signals, collected at a wide variety of distances to the shooter, frequently do not cross-correlate well.        3. Because bullet-muzzle spacing varies on each sensor depending on its position relative to the shooter and the shooter's aim point, direct cross-correlation of audio signals involving bullet and muzzle pulses will always yield poor results.        
In sum, there is a need for solutions that may adequately process acoustic signals and overcome such drawbacks, for example, systems and methods that require less communication bandwidth, less processing power, and/or perform better than those using existing processing/correlation techniques.